Expert Team Lead, Medicine
x.ai · Australia, Canada, United States · AU,CA,US
Health Tech
Remote
physician
Nurse
Pharmacist
Dentist
Demand82
Career growth78
Healthcare fit88
Remote potential65
Salary band
USD 104k – 170k
5-year outlook
Likely competitive with AI/health-tech data operations roles and may exceed typical clinical salaries, but compensation is not disclosed and could be equity-heavy or variable. Long-term growth depends on scaling into AI program management, clinical informatics, or health-tech leadership.
Clinical license
Not required
Applicant reach
moderate
Seniority
lead
Employment type
full-time
Date found
2026-10-02
Intelligence details
Flexible work details
- Engagement type
- Permanent
- Hours
- Full-time
- Eligible countries
- Australia, Canada, United States
- Profession fit
- physician, Nurse, Pharmacist, Dentist
- Rate period
- Annual
Listing via Himalayas.
Eligibility, licensing, and location restrictions can change. Always confirm details on the source posting before applying.
Why this is worth applying to
Worth applying for clinicians with data labeling, annotation, or AI evaluation experience who want a hands-on AI/health-tech leadership role. Less compelling for those without labeling experience or who want direct clinical practice.
Who should apply
MD/DO/MBBS/PharmD/DDS/PhD clinicians, nurses, public health or health administration graduates, and IMGs with clinical data familiarity plus 8+ months in annotation, AI training/evaluation, or content quality; especially those with people leadership or QA experience.
CV angle
Frame clinical training as domain expertise for medical AI data quality: highlight experience with EHRs, labs, imaging, clinical documentation, guideline adherence, taxonomy, annotation/evaluation, and quality metrics. Show leadership through coaching, performance reviews, process improvement, and cross-functional collaboration; avoid claiming non-clinical experience you do not have.
Skills to highlight
- Clinical data interpretation
- Medical terminology and documentation
- Data labeling and annotation
- AI model evaluation and quality assurance
- Guideline adherence and taxonomy management
- People leadership and coaching
- Process improvement and KPI tracking
- Cross-functional collaboration with engineering/product
Role summary
Lead a team of AI Tutors who create, review, and evaluate medical-domain training data for AI models. The role combines hands-on labeling/review, quality assurance, people management, and process improvement to ensure high-quality clinical AI data at scale.
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